Gender: Female 
Age: 35-44
Nationality: United States
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: Undergraduate degree
Father's education: Prefer not to say
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Not employed, but looking for work
Occupation: Prefer not to say
Mother's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Father's occupation: Prefer not to say
Hobbies: Listen to rock/indie music;Listen to hiphop and rap;Exercise;Use social media;Go to museums and galleries;Do arts and crafts;Watch dance or ballet 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Rarely
LLMs used: Character.AI;ChatGPT;Google Gemini 
LLM use cases: Paraphrasing or finding synonyms;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Answering questions about general knowledge;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Entertainment;Personal;Creative or artistic 
Prompt 1: Look for grammar errors in this text
Prompt 2: How can this paragraph be more descriptive
Prompt 3: When was the first cell phone invented
Prompt 4: How to find my W-2 online
Prompt 5: Set a timer for 20 minutes